Processors keep shrinking and getting smarter. What are the implications of how IoT modules are integrating sensors and processors? What is the implication of new device design? Where does the edge give applications the most benefit?

Intelligent gateways bring the value of the cloud to solutions that require evaluation and analytics. Does the use of the gateways reduce the cost of cloud services? What applications can’t afford the delay in cloud processing? Do intelligent gateways reduce the cost and problem of legacy systems when implementing intelligent edge solutions?

We used to say the network is dumb, but as solutions such as Network APIs, SDN and NFV have shown, the network is rich with capabilities. When it comes to IoT, the smart network offers a variety of features such as security, and cost control. Who are the leaders in supporting IoT with intelligent connectivity?

The Intelligent IoT Cloud Cloud computing enables “As a Service” solutions that has given birth to many an IoT service. As more intelligence goes the edge the need is for a better balance to interfacing with the cloud. Microservices are being designed to bridge the gap. What interfaces are needed for success? Do companies feel they have to choose between the edge and cloud?

This panel discussion will kick off our show by looking to the future. We will discuss the possibility of self-aware IoT and what Intelligence really means with respect to IoT and how it can leverage data, analytics and machine learning.

Is the innovator’s dilemma playing out in the IoT industry? We have many companies that have been in the business of IoT before IoT was called IoT. We also have new entrants that are benefitting from VC’s unicorn investments. Hear about the competitive strategies in a market that is so dynamic.

IT and OT need to find common ground as the use of analytics, digital twins, and machine learning enable process innovation. What are we learning about IoT’s role in innovation? How does the growing intelligence transform operations and implementations across the industry?

Machines have helped humans do amazing things through control and communication. The addition of machine learning and rich analytics enables machines to make critical decisions without human interaction. What are the compelling requirements for humans to delegate processes to machines and what are the concerns?

What happens when Moore’s Law, Cooper’s Law and Metcalf’s Law converge? The answer is the edge gets intelligent and the network increases its capacity to transmit. Traditionally the goal has been to minimize the bandwidth use, but these goals may be a thing of the past. Find out how the ability to transmit more data faster, and process data closer to the edge changes the IoT’s use cases. Will legacy systems stay as is, or having it built, will new solutions take advantage of the dynamics?

Nowhere does IoT have more applications and stricter requirements that in the auto industry. With mapping technology enablement being integrated into GPS, driver assistance, entertainment and diagnostics, we have more sensors and computing being packed into a single space. With all the complexity, the industry sees their implementation as a competitive advantage. This panel looks for the best practices that the industry can agree upon to implement, and the innovation that keeps them apart.

As the edge becomes more intelligent, the communication strategy becomes one of enabling peers to share and react intelligently. These networks require additional design for security and analytics. What are the security risks? What are the advantages of near real-time collective analytics?

Security is the topic that everyone complains about, but no one listens to the solutions. This session is looking to change that by looking at the requirements. How can advances in machine learning change the capabilities of detection, command and control.

Being Smart is about more than access to and collection of Data. To truly reach Smart City status, municipalities must leverage analytics to make its volumes of data actionable and lead to improved operations and a happier, more invested citizenry.